Today’s, and near future, communication networks rely heavily on capacity expansion to keep pace with the massive number of mobile devices and ever-increasing mobile traffic. This expansion can be achieved through three major ingredients, namely, adding more wireless-spectrum, efficient usage of this spectrum, and adequate networks’ architectures. In this paper, a proposition for integrating these three ingredients in a cognitive-radio-inspired framework is presented. The focus is on the integration of the idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. This framework is based on a conceptual network-architecture articulated with a generic and cooperative spectrum-harvesting scheme. The former brings the necessary agility for such heterogeneous environments, the latter keeps the network supplied with the vital spectrum resources. In our proposal, we make use of cross-correlated sequences (CCSs) for context-aware events’ signaling purposes. This choice is motivated by the particularly interesting characteristics of CCSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.

Due to the intrinsically geo-distributed subcontracting maintenance activity practice, the maintenance scheduling has for a long time been a major challenge in the industry. This research work presents a methodology to schedule the maintenance activities of geo-distributed assets. A multi-agent system based approach is proposed to enable the decision-making for the subcontractors in a distributed industrial environment under uncertainty. An auction based negotiation mechanism is designed to promote competition and cooperation among the different agents, and to obtain global good schedule.Compared to the Weighted Shortest Processing Time first–Heuristic–Earliest Due Date (WSPT-H-EDD) method, the experimental results show that the proposed approach is able to provide scheduling scheme with good performances in terms of Global Cost, Total Weighted Tardiness Cost and makespan.

Securing the network communication represents one of the most important challenges in wireless sensor networks. The key distribution problem has been widely discussed in classical wireless sensor networks contrarily to heterogeneous ones. HWSNs (Heterogeneous Wireless Sensor Networks) have optimized the network capability and opened new security opportunities by introducing high resource capacity sensor nodes in the network. In this paper, an efficient dynamic authentication and key Management scheme is proposed for heterogeneous WSN. The main idea is to provide a single lightweight protocol for both authentication and key establishment while optimizing the security level. The key distribution algorithm is based on preexisting information to generate dynamic keys and does not require any secure channel and sharing phase which improves the security, energy efficiency and reduces the memory consumption. Experimental results have confirmed the performances of our mechanism compared to some of the existing security protocols.

Actually, wireless sensor networks represent a substantial part in IoT. However, their limitation requires a special consideration in IoT applications. For their integration with the internet, it is necessary to adapt such networks using different middleware, with taking into account various challenges such as heterogeneity and interoperability.

Previously Service Oriented Architecture (SOA) was the suitable design, but with a better practice, a new design called microservice becomes the leader due to its high performance and its suitability for IoT applications.

In this paper, we first survey the most important middleware that have been proposed to handle WSN through IoT. Also, we discuss the most crucial microservices that handle different integration factors by making them supported by the proposed middleware. Our proposal is inspired from artificial neural network architecture to allow dynamic service interaction; it supports unlimited services with a regard to various device capabilities separately of the cloud technologies. Moreover, the evaluation of our design clearly shows that our middleware allows a lightweight WSN integration with IoT regarding to their limitations and requirements.

Identification schemes based on multivariate polynomials have been receiving attraction in different areas due to the quantum secure property. Identification is one of the most important elements for the IoT to achieve communication between objects, gather and share information with each other. Thus, identification schemes which are post-quantum secure are significant for Internet-of-Things (IoT) devices. Various polar forms of multivariate quadratic and cubic polynomial systems have been proposed for these identification schemes. There is a need to define polar form for multivariate dth degree polynomials, where d ≥ 4 . In this paper, we propose a solution to this need by defining constructions for multivariate polynomials of degree d ≥ 4 . We give a generic framework to construct the identification scheme for IoT and RFID applications. In addition, we compare identification schemes and curve-based cryptoGPS which is currently used in RFID applications.

Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions.

Diabetic patients are prone to daily and severe health-related risks, namely hyper and hypoglycaemia. Hypoglycaemia phenomenon happens when the glucose level in patient's blood is lower than a well-determined sill. It may induce serious impacts, such as functional brain failure or even the death. Hypoglycaemia is especially dangerous when it occurs during the night while the patient is asleep because it becomes difficult to be detected by the patient itself or other persons around him. While all existing sensor-based solutions are detection-only driven, the proposed solution goes beyond and attempts to treat autonomously, and at low cost, the nocturnal hypoglycaemia. The presented system detects the nocturnal hypoglycaemia phenomenon based on accelerated heart-rate symptom and a progressive detection algorithm. The system treats then the detected nocturnal hypoglycaemia throughout safe and automatic injection of glucagon.

This article describes how fault tolerance is an essential issue for many WSN (Wireless Sensor Network) applications such as wildlife monitoring, battlefield surveillance and health monitoring. It represents a great challenge for researchers regarding to the characteristics of sensor nodes which are prone to failures due essentially to their limited resources. Faults may occur, not only when sensor nodes exhaust their energy, but also when the congestion phenomenon emerges, because of a high traffic in the network and limited storage capacity of the sensor nodes. In order to support fault tolerance in WSNs, the authors propose a new scheme which incorporates a link quality estimation algorithm and a congestion detection mechanism to enable nodes that present high quality links to be chosen for routing in a non-congested area in case of faults. Evaluations through simulations under NS2 show that our proposed protocol tolerates faults with a minimum cost relatively to HEEP protocol and improves network's performances comparatively to other fault tolerant protocols such as EF-LEACH.

Security is one of the major challenges in the design and implementation of protocols for mobile ad hoc networks (MANETs). In such systems, the cooperation between nodes is one of the important principles being followed in the current research works to formulate various security protocols. Many existing works assume that mobile nodes will follow prescribed protocols without deviation. However, this is not always the case, because these networks are subjected to a variety of malicious attacks. Since there are various models of attack, trust routing scheme can guarantee security and trust of the network. The purpose of this paper is to propose a novel trusted routing model for mitigating attacks in MANETs.

Massive capacity demand is a major impetus behind the advances, in various ways, of today and near future wireless communication networks. To face this challenge, more wireless spectrum is needed, efficient usage of this spectrum is necessary, and adequate architectures are required. In this paper, we present a conceptual solution based on a cognitive-radio-inspired cellular network, for integrating idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. We describe the conceptual architecture of this integrating network, referred to as Integrating cognitive-radio-inspired cellular network (I-CRICNet), and present a cooperative spectrum-harvesting scheme that keeps the former supplied with spectrum resources. In the latter scheme, we make extensive use of cross-correlated sequences (CSSs), for events signaling purposes. This choice is motived by the particularly interesting characteristics of the CSSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.

Reliable data transport is an essential requirement for many multimedia applications in wireless sensor networks. Actually, an efficient transport protocol for these applications must take into account not only reliability and energy consumption factors but also memory occupancy and data delivery delay. Recently, many research works have been conducted in this area, however the proposed protocols treat some of these aspects and neglect others. Contrarily, in this paper we present a novel transport solution designed to provide 100% reliability without making light of other factors. Through different mechanisms, we attempt to reach this objective with congestion avoidance and good performances in terms of energy consumption, delivery delay, and memory storage. The proposed protocol, called congestion avoidance with reliable transmission and energy efficiency (CARTEE), attains these goals through several mechanisms, namely: fixed sliding window transmission, alternative implicit/explicit acknowledgement, a new congestion detection technique, and distributed transmission rate adjustment. To evaluate the proposed protocol, we have conducted simulations using ns-3. The obtained results confirm the efficiency and scalability of CARTEE and demonstrate that it outperforms the recent proposed transport protocols in terms of reliability, congestion avoidance, data cache occupancy, and latency.

The interest shown by some community of researchers to autonomous drones or UAVs (unmanned aerial vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we proposed a flocking-based routing protocol for UAVs called BR-AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. Moreover, an automatic ground base stations discovery mechanism has been introduced for a proactive drones and ground networks association needed for the context of real-time applications. The performance of BR-AODV was evaluated and compared with that of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.

Examines the market for wireless sensor networks in the era and expansion of the Internet of Things. Over the past decade, the fast expansion of the Internet of Things (IoT) paradigm and wireless communication technologies has raised many scientific and engineering challenges that call for ingenious research efforts from both academia and industry. The IoT paradigm now covers several technologies beyond RFID and wireless sensor networks (WSNs). In fact, the number of potential application fields has already exceeded expectations. According to Cisco IBSG, more than 50 billion devices are expected to be connected to the Internet by 2020, with around 20 percent from the industry sector. Therefore, integrating the IoT concept and industrial WSNs (IWSNs) is an attractive choice for industrial processes, which may optimize operational efficiency, automation, maintenance, and rationalization. Moreover, IoT ensures large-scale interconnection between machines, computers, and people, enabling intelligent industrial operations. This emergent technological evolution has led to what has become the Industrial IoT (IIoT). IIoT will bring promising opportunities, along with new challenges.

The emergence of new data handling technologies and analytics enabled the organization of big data in processes as an innovative aspect in wireless sensor networks (WSNs). Big data paradigm, combined with WSN technology, involves new challenges that are necessary to resolve in parallel. Data aggregation is a rapidly emerging research area. It represents one of the processing challenges of big sensor networks. This paper introduces the big data paradigm, its main dimensions that represent one of the most challenging concepts, and its principle analytic tools which are more and more introduced in the WSNs technology. The paper also presents the big data challenges that must be overcome to efficiently manipulate the voluminous data, and proposes a new classification of these challenges based on the necessities and the challenges of WSNs. As the big data aggregation challenge represents the center of our interest, this paper surveys its proposed strategies in WSNs.

Recently, multimedia streaming applications are deployed anywhere (homes, campuses, etc.). Delivering these applications over mobile ad hoc networks is a challenging task: first, mobile ad hoc networks are infrastructure less, with dynamic topology, and limited resources. Secondly these applications have strict quality of service (QoS) requirements given with delay, jitter, bandwidth, loss rate, etc. Several architectures have been developed. However, an important part like QoS in routing level is still omitted. In this paper, many different coding techniques for video streaming are reviewed and two routing protocols (reactive and proactive) are used to evaluate which of them can improve QoS for multimedia streaming applications. Results show that reactive protocol performs better than proactive protocol in terms of throughput and network load in high mobility, but roles are reversed in terms of loss rate and network load for large-scale networks. PNSR and Jitter are influenced by nodes numbers independently of used protocol.